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All Journal Jurnal Ilmu Komputer dan Agri-Informatika Bulletin of Computer Science Research Mejuajua Aksi Kita: Jurnal Pengabdian Kepada Masyarakat
Rossy Nurhasanah
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Economics, Econometrics & Finance Environmental Science Languange, Linguistic, Communication & Media Public Health Social Sciences Other

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Penerapan Probabilistic Neural Network pada Klasifikasi Patogen Daun Bibit Jabon Berdasarkan Ciri Morfologi Spora Melly Br Bangun; Yeni Herdiyeni; Elis Nina Herliyana; Rossy Nurhasanah
Bulletin of Computer Science Research Vol. 4 No. 2 (2024): Februari 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v4i2.325

Abstract

The aim of this research is to clasify pathogen of Jabon’s leaf seedling based on spora morphological features using Probabilistic Neural Network classifier. Three types of pathogen to be classified are Colletotrichum sp., Curvularia sp., and Fusarium sp.. The methodologies used are data acquisition using optilab camera microscope to obtain microscopic image data , preprocessing (grayscale, median smoothing, thresholding Otsu, region filling, median smoothing and dilate), morphology feature extraction (area, perimeter, area convex, convex perimeter, compactness, solidity, convexity and roundness), Probabilistic Neural Network classification, and evaluation. The basic morphological characteristics consisting of area, perimeter, convex area, convex perimeter, and derived morphological characteristics consisting of compactness, solidity, convexity and roundness. The experimental results of the morphological feature extraction showed that the compactness and roundness characteristics can be used to identify the three types of pathogens because with these characteristics each class of pathogen is separate. Testing for this research was carried out using 150 test data from three classes of objects from the dataset, namely class 1 (Colletotrichum sp.), class 2 (Curvularia sp.), and class 3 (Fusarium sp.). Then the results of pathogen classification using the application of the PNN algorithm in testing this research obtained an average accuracy value of 86.8% with a proportion of training data and test data of 80:20. The results of the PNN classification on 150 test data were that there were 36 data classified into Colletotrichum sp., 44 data classified into Curvularia sp., and 50 data classified into Fusarium sp. Further research could be done with the identification of digital microscopic images without cropping and systems that could clasify a colony image of pathogens clearly.
Topic Modelling on Beauty Product Reviews Using Latent Dirichlet Allocation Ade Sarah Huzaifah; Huzaifah, Ade Sarah; Rossy Nurhasanah; R. A. Fattah Adriansyah
Jurnal Ilmu Komputer dan Agri-Informatika Vol. 12 No. 1 (2025)
Publisher : Sekolah Sains Data, Matematika, dan Informatika. Institut Pertanian Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jika.12.1.119-131

Abstract

In contemporary society, beauty products have become essential, particularly for women. With their growing popularity, online review platforms now provide extensive information on product trends, customer satisfaction, and performance. However, the sheer volume of available reviews presents challenges in drawing meaningful conclusions. To address this, topic modeling techniques such as Latent Dirichlet Allocation (LDA) have been widely employed in text mining and information retrieval. LDA is a probabilistic model capable of uncovering latent structures within textual data and identifying similarities across documents. Recent studies suggest that topic modeling of product reviews in the cosmetics industry can yield valuable insights into consumer perceptions and product attributes. This study aims to identify thematic patterns in customer reviews of ten facial cleanser brands sourced from the Female Daily website. The research methodology consists of five main stages: data collection, preprocessing, topic modeling using LDA, visualization, and topic interpretation. The results reveal that Topic 2, which highlights preferred product advantages, is the most frequently discussed, accounting for 48.5% of the total reviews. Topic 1, which focuses on the effects of products on acne-prone skin, constitutes 38%, while Topic 3, emphasizing products with natural ingredients, makes up 13.5% of the reviews. These findings can assist businesses in developing products that align more closely with consumer preferences. Moreover, they support prospective buyers in making informed purchasing decisions by enhancing their understanding of product attributes based on user experiences
Enhancing Understanding of AI-Based Digital Business Through Interactive Seminars for Information Technology Students Ade Sarah Huzaifah; Rossy Nurhasanah; Fanindia Purnamasari; Dedy Arisandi; Ivan Jaya
Aksi Kita: Jurnal Pengabdian kepada Masyarakat Vol. 1 No. 4 (2025): AGUSTUS
Publisher : Indo Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63822/vk045k91

Abstract

The development of artificial intelligence (AI) technology has become a major driver in the transformation of the digital business world, including in the startup sector. However, a deep understanding of AI integration into business models remains a challenge for students, particularly in the field of Information Technology (IT). This community service activity aims to enhance the knowledge and skills of IT students in designing strategic, ethical, and sustainable AI-based digital businesses. The implementation method involves a one-day educational seminar, including presentations, interactive discussions, simulations of Business Model Canvas (BMC) development, and evaluation through questionnaires. Evaluation results showed significant improvements: understanding of the BMC increased from 41% to 89%, understanding of AI startup concepts from 54% to 92%, ability to draft a business plan from 16% to 78%, and motivation for technology entrepreneurship from 68% to 90%. These findings indicate that an applied and participatory approach in seminars is effective in developing digital entrepreneurship capacity among IT students.
COMMUNITY-BASED PRODUCTION OF LIQUID SMOKE AS A NON-CARCINOGENIC FISH PRESERVATIVE: - Taufik, Muhammad; Boby Cahyady; Rossy Nurhasanah; Masruroh, Pingkan; Syahputra, Muhammad Rizky; Azzahrah, Nabilah Azka; Zul Alfian; Mariany Razali
Mejuajua: Jurnal Pengabdian pada Masyarakat Vol. 5 No. 2 (2025): Desember 2025
Publisher : Yayasan Penelitian dan Inovasi Sumatera (YPIS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52622/mejuajuajabdimas.v5i2.297

Abstract

The growing demand for safe fish preservatives has encouraged the use of liquid smoke as an alternative to high-temperature processing, which may form carcinogenic compounds. This community service program focused on producing coconut-shell-based liquid smoke through pyrolysis followed by distillation to obtain grade-2 liquid smoke. Acetic acid content was determined using alkalimetry with 0.1 N NaOH. The results showed an increase in acetic acid concentration from 1% to 6.5%, meeting the grade-2 standard of SNI 8985:2021. Application through 20-minute immersion preserved fish quality for up to three days without generating carcinogenic properties. Beyond product development, the program strengthened local socio-economic conditions by providing training, empowering residents to produce liquid smoke independently, and opening new micro-enterprise opportunities. This demonstrates that community-based production can supply safe, standardized preservatives while enhancing economic resilience in Manunggal Village.
Co-Authors Ade Sarah Huzaifah Azzahrah, Nabilah Azka Boby Cahyady Dedy Arisandi Elis Nina Herliyana Fanindia Purnamasari Huzaifah, Ade Sarah Ivan Jaya Mariany Razali Masruroh, Pingkan Melly Br Bangun MUHAMMAD TAUFIK R. A. Fattah Adriansyah Syahputra, Muhammad Rizky Zul Alfian